let commit_hash = AWAIT FORK implement-experiment experiment_name fail_path?.
let setup_ok = AWAIT FORK setup-experiment commit_hash.
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| <title>End-to-End Hierarchical Memory — A system design for billion-token attention</title> | |
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| #!/usr/bin/env bash | |
| # Chat with imposter-72b on kurtz (Qwen2.5-72B + LoRA via vLLM) | |
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| <html><head><meta charset="utf-8"><title>VOID Maintenance Cron Prompt</title> | |
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| <html><head><meta charset="utf-8"><title>VOID Recursive Forecaster — Results</title> | |
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AttnRes replaces the standard residual connection in transformers with a depth attention mechanism — instead of simply adding each layer's output to a running sum, the model attends over previous layer outputs to decide what information to carry forward.
Standard transformers use x = x + layer(x) at every layer. AttnRes variants replace this with a learned attention operation across the depth axis: "which previous layers' outputs should I attend to when constructing the input to this layer?"
All experiments use a GPT-2-style decoder-only transformer trained on FineWeb-Edu (10B tokens), with RoPE, SwiGLU, and RMSNorm.